Automated transaction processing based on cognitive learning

Abstract

Aspects of the disclosure relate to systems for processing transactions between two entities. A transaction control platform may determine attributes associated with different transfer channels between the two entities. Based on the determined attributes, the transaction control platform may determine a transfer channel to be used for transmitting a message corresponding to the transaction. The transaction control platform may use machine learning algorithms to identify an optimal transfer channel that meets particular desired factors.

I claim: 
     
       1. A method for transferring funds from a payer to a payee based on a transmission of an electronic message from the payer to a financial institution associated with the payer, the method comprising:
 receiving, via a communication interface, a first message indicating a first request to process a fund transfer via a first transfer channel of a plurality of available transfer channels, the first message indicating a first request to process a funds transfer via a first transfer channel computing device in electronic communication with a transaction control computing platform, wherein the first transfer channel computing device is configured to transfer the funds based on the first request to a destination account of the payee maintained at a payee financial institution having a destination computing device in electronic communication with the first transfer channel computing device, 
 wherein the first request comprises transaction details associated with the funds transfer including a transaction type, 
 wherein the transaction type is associated with the first transfer channel and indicates that the first transfer channel of the plurality of available transfer channels is to be used for the funds transfer, 
 wherein the first transfer channel comprises a system queue for storing one or more fund transfer requests which are processed in an order specified by the system queue, 
 wherein the transaction control computing platform comprises a transaction analytics computing unit for monitoring funds transfer attributes associated with the plurality of available transfer channels and for storing determined attributes in a log file and periodically updating the log file based on the determined attributes and the monitoring, and 
 wherein the funds transfer attributes are associated with at least one of a cost, timing and efficiency of transfer channels; 
 determining from the first request that the first transfer channel of the plurality of available transfer channels is to be used for processing the first request; 
 determining respective attributes of the other available transfer channels; 
 monitoring a real-time status of the attributes of the first transfer channel to detect when the first transfer channel does not meet at least one criteria based on the first message; 
 selecting, in response to the monitoring and based on a real-time status of the attributes of the other available transfer channels and the first message, a second transfer channel of the other available transfer channels; 
 switching from the first transfer channel to the second transfer channel to ensure a successful transfer of funds; and 
 transmitting, via the communication interface and via the second transfer channel, a second message indicating a second request to process the funds transfer, wherein the transaction control computing platform selects the second transfer channel based on a machine learning algorithm to determine one or more payment systems and intermediary accounts for the funds transfer and to determine at least one of wait times, expected usage costs, operation status, country based restrictions, and customer satisfaction scores associated with the second transfer channel, 
 wherein the machine learning algorithm of the transaction control computing platform comprises an artificial neural network configured to execute the machine learning network to determine a real-time status of the attributes of each of the available transfer channels, 
 wherein an artificial neural network obtains attribute information about the available transfer channels through a plurality of input nodes comprising logical inputs from different data sources, wherein a plurality of first output signals from the input nodes are processed by a plurality of processing nodes, wherein the processing nodes comprise a plurality of parallel processes executing on multiple computing devices, wherein each of the processing nodes may be connected to one or more other processing nodes, wherein the connections connect an output of one node to an input of another node, wherein the connection is correlated with a weighting value in which the output may be weighted as more important or significant than an output of another processing node, thereby influencing a degree of further processing as an input traverses across the artificial neural network, wherein the connections are modified by data feedback of correct or incorrect decisions such that the artificial neural network learns and is dynamically reconfigured as more inputs are processed, and 
 wherein one or more second output signals from the plurality of processing nodes are processed by a plurality of output nodes to obtain attribute status information about the available transfer channels, wherein the output comprises at least one determined transfer channel(s), expected wait times, threshold queue lengths, threshold times, predicted expected handshake wait times, threshold customer satisfaction scores, confidence values, operation status of transfer channels, predicted expected usage costs, and classification output. 
 
     
     
       2. The method of  claim 1 , wherein the first message indicates at least one selected from:
 a destination user account for the fund transfer; 
 an intermediary account for the fund transfer; 
 the first transfer channel; 
 a payment system associated with the first transfer channel; 
 origin currency associated with the fund transfer; 
 destination currency associated with the fund transfer; 
 a cut-off time associated with the fund transfer; 
 a value of the fund transfer; and 
 combination thereof. 
 
     
     
       3. The method of  claim 2 , further comprising determining, based on the first message, an expected wait time for completing the fund transfer over the first transfer channel, wherein the selecting the second transfer channel is based on determining that the expected wait time for completing the fund transfer over the first transfer channel exceeds the cut-off time. 
     
     
       4. One or more non-transitory computer-readable media for transferring funds from a payer to a payee based on a transmission of an electronic message from the payer to a financial institution associated with the payer and storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:
 receive, via the communication interface, a first message indicating a first request to process a fund transfer via a first transfer channel of a plurality of available transfer channels, the first message indicating a first request to process a funds transfer via a first transfer channel computing device in electronic communication with a transaction control computing platform, wherein the first transfer channel computing device is configured to transfer the funds based on the first request to a destination account of the payee maintained at a payee financial institution having a destination computing device in electronic communication with the first transfer channel computing device, 
 wherein the first request comprises transaction details associated with the funds transfer including a transaction type, 
 wherein the transaction type is associated with the first transfer channel and indicates that the first transfer channel of the plurality of available transfer channels is to be used for the funds transfer, 
 wherein the first transfer channel comprises a system queue for storing one or more fund transfer requests which are processed in an order specified by the system queue, 
 wherein the transaction control computing platform comprises a transaction analytics computing unit for monitoring funds transfer attributes associated with the plurality of available transfer channels and for storing determined attributes in a log file and periodically updating the log file based on the determined attributes and the monitoring, and 
 wherein the funds transfer attributes are associated with at least one of a cost, timing and efficiency of transfer channels; 
 determine from the first request that the first transfer channel of the plurality of available transfer channels is to be used for processing the first request; 
 determine respective attributes of the other available transfer channels; 
 monitor a real-time status of the attributes of the first transfer channel to detect when the first transfer channel does not meet at least one criteria based on the first message; 
 select, in response to the monitoring and based on a real-time status of the attributes of the other available transfer channels and the first message, a second transfer channel of the other available transfer channels; 
 switch from the first transfer channel to the second transfer channel to ensure a successful transfer of funds; and 
 transmit, via the communication interface and via the second transfer channel, a second message indicating a second request to process the funds transfer, wherein the transaction control computing platform selects the second transfer channel based on a machine learning algorithm to determine one or more payment systems and intermediary accounts for the funds transfer and to determine at least one of wait times, expected usage costs, operation status, country based restrictions, and customer satisfaction scores associated with the second transfer channel, 
 wherein the machine learning algorithm of the transaction control computing platform comprises an artificial neural network configured to execute the machine learning network to determine a real-time status of the attributes of each of the available transfer channels, 
 wherein an artificial neural network obtains attribute information about the available transfer channels through a plurality of input nodes comprising logical inputs from different data sources, 
 wherein a plurality of first output signals from the input nodes are processed by a plurality of processing nodes, wherein the processing nodes comprise a plurality of parallel processes executing on multiple computing devices, wherein each of the processing nodes may be connected to one or more other processing nodes, wherein the connections connect an output of one node to an input of another node, wherein the connection is correlated with a weighting value in which the output may be weighted as more important or significant than an output of another processing node, thereby influencing a degree of further processing as an input traverses across the artificial neural network, wherein the connections are modified by data feedback of correct or incorrect decisions such that the artificial neural network learns and is dynamically reconfigured as more inputs are processed, and 
 wherein one or more second output signals from the plurality of processing nodes are processed by a plurality of output nodes to obtain attribute status information about the available transfer channels, wherein the output comprises at least one determined transfer channel(s), expected wait times, threshold queue lengths, threshold times, predicted expected handshake wait times, threshold customer satisfaction scores, confidence values, operation status of transfer channels, predicted expected usage costs, and classification output. 
 
     
     
       5. The one or more non-transitory computer-readable media of  claim 4 , wherein the first message indicates at least one selected from:
 a destination user account for the fund transfer; 
 an intermediary account for the fund transfer; 
 the first transfer channel; 
 a payment system associated with the first transfer channel; 
 origin currency associated with the fund transfer; 
 destination currency associated with the fund transfer; 
 a cut-off time associated with the fund transfer; 
 a value of the fund transfer; and 
 combination thereof. 
 
     
     
       6. The one or more non-transitory computer-readable media of  claim 5 , storing instructions that, when executed by a computing platform further cause the computing platform to:
 determine, based on the first message, an expected wait time for completing the fund transfer over the first transfer channel, wherein the selecting the second transfer channel is based on determining that the expected wait time for completing the fund transfer over the first transfer channel exceeds the cut-off time. 
 
     
     
       7. An apparatus for transferring funds from a payer to a payee based on a transmission of an electronic message from the payer to a financial institution associated with the payer, the apparatus comprising:
 at least one processor; 
 a communication interface communicatively coupled to the at least one processor; and 
 a memory storing computer-readable instructions that, when executed by the at least one processor, cause the apparatus to: 
 receive, via the communication interface, a first message indicating a first request to process a fund transfer via a first transfer channel of a plurality of available transfer channels, the first message indicating a first request to process a funds transfer via a first transfer channel computing device in electronic communication with a transaction control computing platform, wherein the first transfer channel computing device is configured to transfer the funds based on the first request to a destination account of the payee maintained at a payee financial institution having a destination computing device in electronic communication with the first transfer channel computing device, 
 wherein the first request comprises transaction details associated with the funds transfer including a transaction type, 
 wherein the transaction type is associated with the first transfer channel and indicates that the first transfer channel of the plurality of available transfer channels is to be used for the funds transfer, 
 wherein the first transfer channel comprises a system queue for storing one or more fund transfer requests which are processed in an order specified by the system queue, 
 wherein the transaction control computing platform comprises a transaction analytics computing unit for monitoring funds transfer attributes associated with the plurality of available transfer channels and for storing determined attributes in a log file and periodically updating the log file based on the determined attributes and the monitoring, and 
 wherein the funds transfer attributes are associated with at least one of a cost, timing and efficiency of transfer channels; 
 determine from the first request that the first transfer channel of the plurality of available transfer channels is to be used for processing the first request; 
 determine respective attributes of the other available transfer channels; 
 monitor a real-time status of the attributes of the first transfer channel to detect when the first transfer channel does not meet at least one criteria based on the first message; 
 select, in response to the monitoring and based on a real-time status of the attributes of the other available transfer channels and the first message, a second transfer channel of the other available transfer channels; 
 switch from the first transfer channel to the second transfer channel to ensure a successful transfer of funds; and 
 transmit, via the communication interface and via the second transfer channel, a second message indicating a second request to process the funds transfer, wherein the transaction control computing platform selects the second transfer channel based on a machine learning algorithm to determine one or more payment systems and intermediary accounts for the funds transfer and to determine at least one of wait times, expected usage costs, operation status, country based restrictions, and customer satisfaction scores associated with the second transfer channel, 
 wherein the machine learning algorithm of the transaction control computing platform comprises an artificial neural network configured to execute the machine learning network to determine a real-time status of the attributes of each of the available transfer channels, 
 wherein an artificial neural network obtains attribute information about the available transfer channels through a plurality of input nodes comprising logical inputs from different data sources, 
 wherein a plurality of first output signals from the input nodes are processed by a plurality of processing nodes, wherein the processing nodes comprise a plurality of parallel processes executing on multiple computing devices, wherein each of the processing nodes may be connected to one or more other processing nodes, wherein the connections connect an output of one node to an input of another node, wherein the connection is correlated with a weighting value in which the output may be weighted as more important or significant than an output of another processing node, thereby influencing a degree of further processing as an input traverses across the artificial neural network, wherein the connections are modified by data feedback of correct or incorrect decisions such that the artificial neural network learns and is dynamically reconfigured as more inputs are processed, and 
 wherein one or more second output signals from the plurality of processing nodes are processed by a plurality of output nodes to obtain attribute status information about the available transfer channels, wherein the output comprises at least one determined transfer channel(s), expected wait times, threshold queue lengths, threshold times, predicted expected handshake wait times, threshold customer satisfaction scores, confidence values, operation status of transfer channels, predicted expected usage costs, and classification output. 
 
     
     
       8. The apparatus of  claim 7 , wherein the first message indicates at least one selected from:
 a destination user account for the fund transfer; 
 an intermediary account for the fund transfer; 
 the first transfer channel; 
 a payment system associated with the first transfer channel; 
 origin currency associated with the fund transfer; 
 destination currency associated with the fund transfer; 
 a cut-off time associated with the fund transfer; 
 a value of the fund transfer; and 
 combination thereof. 
 
     
     
       9. The apparatus of  claim 8 , wherein respective attributes of the available transfer channels comprise at least one selected from:
 lengths of respective system queues; 
 respective usage costs; 
 respective average wait times for completing fund transfers; 
 respective average times for receiving handshake signals; and 
 combination thereof. 
 
     
     
       10. The apparatus of  claim 9 , further comprising determining, based on the first message and the respective attributes, an expected wait time for completing the fund transfer over the first transfer channel, and
 wherein the selecting the second transfer channel is based on determining that the expected wait time for completing the fund transfer over the first transfer channel exceeds the cut-off time. 
 
     
     
       11. The apparatus of  claim 9 , wherein the selecting the second transfer channel is based on determining that a transaction input device has not received a handshake signal, responsive to the first message, from a first computing platform. 
     
     
       12. The apparatus of  claim 9 , wherein the selecting the second transfer channel is based on determining that a length of a system queue associated with the first transfer channel is greater than a threshold queue length. 
     
     
       13. The apparatus of  claim 9 , wherein the selecting the second transfer channel is based on determining that a difference between the cut-off time and an elapsed time following a transmission of the first message is within a threshold time. 
     
     
       14. The apparatus of  claim 13 , wherein the threshold time is determined based on an average time period between transmissions of prior messages indicating requests for fund transfers, to a first computing platform, and receptions of transfer confirmation messages from the first computing platform. 
     
     
       15. The apparatus of  claim 9 , wherein selecting the second transfer channel is based on determining that a first length of a first system queue associated with the first transfer channel is greater than a second length of a second system queue associated with the second transfer channel. 
     
     
       16. The apparatus of  claim 9 , wherein selecting the second transfer channel is based on determining that a first expected wait time for completing fund transfers over the first transfer channel is greater than a second expected time for completing fund transfers over the second transfer channel. 
     
     
       17. The apparatus of  claim 7 , wherein the first transfer channel comprises at least a first payment system and a second payment system, wherein the first payment system comprises a second computing platform, wherein the second payment system comprises a third computing platform, and wherein the computer-readable instructions, when executed by the at least one processor, cause the transaction control computing platform to:
 transmit, via the communication interface to the third computing platform, a third message indicating a third request to process the fund transfer, wherein the selecting the second transfer channel is based on determining that the transaction control computing platform has not received, from the third computing platform, a handshake signal responsive to the third message. 
 
     
     
       18. The apparatus of  claim 7 , wherein the second transfer channel is associated with a higher tier service level than the first transfer channel. 
     
     
       19. The apparatus of  claim 7 , wherein the selecting the second transfer channel of the available transfer channels comprises:
 determining a subset of transfer channels among the available transfer channels; 
 sending, via the communication interface and to a third computing platform, a third message indicating the subset of transfer channels; and 
 receiving a fourth message indicating the second transfer channel. 
 
     
     
       20. The apparatus of  claim 7 , wherein the computer-readable instructions, when executed by the at least one processor, cause the transaction control computing platform to transmit, via the communication interface and to a first computing platform, a third message indicating a request to cancel the first request. 
     
     
       21. The apparatus of  claim 7 , wherein the artificial neural network comprises a feedback system and wherein the feedback system provides one or more third output signals from at least one set of output nodes to at least one input node.